GenBench prepared datasets

This repository contains the exact prepared arrays used by the canonical GenBench training and evaluation runs. It intentionally excludes redundant source archives: every benchmark's Python preparation module records and verifies the original upstream source, while these files are sufficient to train and evaluate the published baselines directly. DeepSTARR's small official activity-predictor weights are included because they are part of its evaluation protocol.

Directory	Generative object	Prepared contents
QM9	Molecular geometries	Packed characterized molecules and TD-jumps split rows
MiniBooNE	Particle events	Literature split and normalization
NavierStokes	Vorticity fields	Fourier-downsampled train/validation/test arrays
JetNet30	Particle clouds	Five-class train/validation/test arrays
DeepSTARR	Enhancer sequences	Splits, activities, metadata, and official predictor weights
GuacaMol	Drug-like molecules	Official non-overlapping ChEMBL splits as canonical-SMILES tokens and exact lengths
SpeechCommands	One-second spoken-word waveforms	Official speaker-disjoint train/validation/test arrays and labels

The analytic spiral and checkerboard benchmarks have no stored dataset; their target distributions are generated exactly by the GenBench Python package.

manifest.json is authoritative. It records the byte size and SHA-256 of every required file. Original licenses and redistribution terms differ by dataset; consult each dataset's metadata and upstream source before reuse. CIFAR-10 and MNIST are deliberately absent because their upstream distributions do not provide an affirmative general redistribution grant.